multicollinearity ridge regression

# Import Libraries
import pandas as pd
from sklearn.linear_model import Ridge

# Data Processing
y=df.pop('Next_Tmin')
X_train, X_test, y_train, y_test = train_test_split(df, y, test_size=0.3)

# Fit the Ridge model
ridge = Ridge(alpha=1.0)
ridge.fit(X_train, y_train)

# Evaluate the model
y_pred = ridge.predict(X_test)
ridge.score(X_test,y_test)